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298 articles for “Clinical Data”
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Medical Science in the Digital Era: A Comprehensive Study on Computing in Healthcare
Abstract: Adding computers to medical science has changed how healthcare is delivered, how research is done, and how well patients do. This article talks about the many ways that computer technology is used in modern medicine, such as for diagnostic imaging, electronic health records (EHRs), telemedicine, surgical robotics, and research that is based on data. Improvements in artificial intelligence (AI) and machine learning have made it possible to make more accurate …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 3, 2024 Read article
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Horizon Scanning and Early Assessment of Health Technologies for the Treatment of Orphan Diseases
Abstract: The theoretical foundations and regulatory framework of the processes of the formation of an effective health technology assessment (HTA) system at the early stages of the life cycle of medicines are analyzed in the article. Particular attention is paid to horizon scanning (HS) and early assessment of expensive innovative drugs utilized for treating rare diseases. In order to inform policymakers, purchasers, and providers (to prioritize MT research, financial, and operational …
Published in International Journal of Brain Sciences · Vol. 1, Issue 1, 2024 · pp. 32–39 Read article
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A Comprehensive Review of CNN-Based Framework for Multi-Sign Detection of Diabetic Retinopathy in Fundus Images Using Public Datasets
Abstract: Diabetic retinopathy (DR) is one of the main causes of vision impairment. Blindness prevention and effective treatment depend on early detection. A thorough deep learning-based framework for the automatic segmentation and simultaneous detection of exudates, hemorrhages, and microaneurysms – three important DR indicators – from retinal fundus images is presented in this work. These three pathological signs’ corresponding annotated image patches, along with background (no-sign) areas, were used to train …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 3, 2025 · pp. 14–23 Read article
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Exploring the Intersection of AI Network Pharmacology and Ayurveda: Innovations in Traditional Medicine
Abstract: Integrative frameworks that integrate traditional medicine and modern computer research are increasingly important for advancing evidence-based, individualized healthcare. One interesting strategy is the combination of Ayurveda, network pharmacology, and artificial intelligence (AI). AI expands the capability by allowing for the quick analysis of biomedical big data, the identification of therapeutic trends, and the optimization of treatment plans. Ayurveda, with its long-standing emphasis on individualized care, holistic balance, and natural remedies, …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 14, Issue 3, 2025 · pp. 92–98 Read article
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Mass Spectrometry–Based Phosphoproteomic Markers to Predict Kinase Inhibitor Response in Solid Tumors
Abstract: Mass spectrometry-based phosphoproteomics has emerged as a powerful tool for predicting kinase inhibitor responses in solid tumors, offering direct functional insights into signaling pathways that surpass traditional genomic profiling by capturing dynamic kinase activities and adaptive resistance mechanisms. Technological breakthroughs, including data- independent acquisition (DIA), trapped ion mobility spectrometry (timsTOF), and efficient enrichment methods like TiO2 or IMAC, now enable comprehensive profiling of over 40,000 phosphorylation sites from limited clinical …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 4, Issue 2, 2026 Read article
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Impact of Diabetes on Quality of Life of Patient with Diabetes in West Tripura
Abstract: Throughout the new millennium, diabetes mellitus is on the rise everywhere. According to IDF, the prevalence of diabetes in worldwide was 537 million in 2021; this number is anticipated to climb to 643 million by 2030 if no effective preventative measures are introduced. According to an IDF research, one in three households has diabetic patients, and one in seven adult diabetics worldwide lives in India. India's percentages were 9.3% in …
Published in Journal of Nursing Science & Practice · Vol. 15, Issue 2, 2025 · pp. 17–28 Read article
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Clone-Specific Drug Delivery Systems: Targeted Approaches and Future Clinical Applications
Abstract: Clone-specific drug delivery systems represent a transformative frontier in personalized medicine, addressing the longstanding challenge of clonal heterogeneity within diseases such as cancer, infectious diseases, and autoimmune disorders. Traditional drug delivery platforms often fail to discriminate between pathogenic and healthy cells, leading to systemic toxicity and reduced therapeutic efficacy. In contrast, clone-specific systems aim to selectively target and eliminate disease-driving cellular clones based on unique molecular signatures, thereby improving treatment …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 21–29 Read article
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Comparative Analysis and Future Research Directions in AI in Healthcare: Medical Imaging and Diagnostics
Abstract: Artificial intelligence (AI) is reshaping healthcare, particularly in the areas of medical imaging and diagnostic practice. By using advanced techniques like machine learning and deep learning, AI systems help improve the accuracy, speed, and effectiveness of identifying diseases and analyzing medical images. This paper provides a comprehensive overview of the application of artificial intelligence in medical imaging and highlights its growing importance in clinical diagnostics. It discusses how AI-based systems …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 8–13 Read article
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Transfer Learning in Deep Learning Models for Medical Imaging: Utilizing Pretrained Models to Improve Performance in Medical Image Analysis
Abstract: Transfer learning is now a trending technique in deep learning, especially in medical imaging. This technique solves landmark problems by utilizing the pre-trained models, including the limited availability of the annotated medical data and the time-consuming computational costs of training deep learning models from scratch. The generalizability of deep models could increase diagnostic precision for specific medical tasks, require fewer samples to train, and take less time to train due …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 1, 2025 · pp. 67–85 Read article
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Advancing Asthma Management: The Synergy of Systems Biology, Artificial Intelligence, and Next-Generation Therapeutics
Abstract: Asthma is an inflammatory disorder of the respiratory tract that is chronic and heterogeneous in nature and has various effects on millions of people. Being a chronic inflammatory disease, asthma remains incurable and the major conventional treatments offer limited success due to the mask nature of its pathophysiology. Systems biology/(AI), and next-generation has greatly enhanced knowledge and the management of asthma. The approaches based on gene, transcript, protein, and metabolite …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 2, 2024 · pp. 1–12 Read article
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Effectiveness of Habb-e-Suranjan and Roghan-e-Farfiyun in the Management of Waja-ul-Rukba (Knee Pain): A Review
Abstract: Introduction: Knee osteoarthritis is a painful condition that represents the degeneration of the cartilage and osteophyte formation in the knee joint, which affects millions of people worldwide. According to the Unani claimed text, accumulation of “madda” (substance) in joints, which is neither absorbed nor expelled, is due to the absence of Quawwat-e-Jazibah (power of absorption) and Quawwat-e-dafia (power of expulsion). Unani medicine presents a promising approach for managing knee osteoarthritis …
Published in Research & Reviews : A Journal of Unani, Siddha and Homeopathy · Vol. 12, Issue 2, 2025 · pp. 7–12 Read article
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Sustainable Advances in Oral Pathology: The Impact of Artificial Intelligence
Abstract: Oral cavity cancers constitute about 4% of all malignant neoplasms. More than 9,900 new cases are reported from the developed countries yearly, and the 5-year mortality rate is higher than 39%. In Europe, the highest rates occur in Hungary, Croatia, and other Central and Eastern European countries; high levels are also seen in India, Pakistan, and Bangladesh. The management of endosseous pathologies presents considerable challenges because they often exhibit no …
Published in Research and Reviews: A Journal of Dentistry · Vol. 16, Issue 1, 2025 · pp. 24–27 Read article
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Cardiovascular Illness Detection and Categorization with Innovative Neural Networks
Abstract: Health-related problems are increasingly prevalent in modern-day societies and are significantly shaped by a multitude of factors encountered in everyday life. Among these, cardiovascular diseases have emerged as one of the primary causes of death on a global scale, posing serious challenges to public health systems. In response to this growing concern, the present study proposes a machine learning-based framework that is not only highly effective but also reliable and …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 21–30 Read article
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Pharmacogenomics in Anesthesia: Case Studies and Clinical Applications for Personalized Care
Abstract: Pharmacogenomics, the study of how genetic variability influences individual responses to medications, is transforming anesthetic practice by enabling personalized care. This case study collection explores the integration of pharmacogenomic insights into anesthesia management, highlighting its impact on safety, efficacy, and patient outcomes. Adverse reactions to anesthetics often arise from genetic polymorphisms that alter drug metabolism or sensitivity. For instance, patients with RYR1 mutations are susceptible to malignant hyperthermia (MH) when …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 15, Issue 2, 2025 · pp. 85–91 Read article
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Skin Cancer Detection System Based on Machine Learning for Recognition of Cancerous Images
Abstract: Skin cancer ranks among the most prevalent types of cancer globally and poses significant risks when left untreated. Skin cancer arises when abnormal cells proliferate uncontrollably in the skin. This uncontrolled growth can be triggered by genetic mutations, exposure to ultraviolet (UV) radiation from the sun or artificial sources like tanning beds, or various other factors. In this, the early detection of cancer plays a crucial role in treatment and …
Published in Research and Reviews: A Journal of Medicine · Vol. 14, Issue 2, 2024 · pp. 1–8 Read article
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High-Definition Electroencephalography: A New Horizon in Neurological Pathology Research
Abstract: The advent of high-density electroencephalography (HD-EEG) has catalyzed a paradigm shift in the exploration of neurological pathologies. This editorial underscore its transformative potential in elucidating brain dynamics and refining diagnostic approaches for a spectrum of conditions, spanning from epilepsy and dementia to cognitive impairments in preterm infants. Our objective is to optimize the utility of HD-EEG by emphasizing the imperative for methodological homogenization and fostering collaborative endeavors. The remarkable spatial …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 2, 2024 · pp. 15–21 Read article
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Study of Lipid Profile and Its Correlation with Coronary Angiogram Finding in a Tertiary Care Hospital in an Urban Setting
Abstract: Coronary artery disease (CAD) is a major global health concern caused by the constriction or blockage of the coronary arteries, which can result in serious cardiovascular events. This study looks at the relationship between lipid profiles and the severity of CAD as measured by coronary angiography in patients in a tertiary care hospital. The study focuses on dyslipidemia as a major risk factor for CAD, emphasizing the importance of efficient …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 14, Issue 3, 2024 · pp. 106–118 Read article
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Nanomedicine in Combination with Artificial Intelligence (AI): Transforming Cancer Treatment
Abstract: The convergence of nanomedicine and artificial intelligence (AI) holds transformative potential for advancing cancer treatment, particularly in liver cancer. Nanomedicine enables the development of targeted drug delivery systems, enhanced imaging modalities, and precise therapeutic interventions, while AI facilitates data-driven decision-making, personalized treatment plans, and predictive analytics. This synergistic approach can significantly improve the diagnosis, treatment, and monitoring of liver cancer by optimizing the use of nanoparticle-based therapies. AI-powered algorithms can …
Published in Trends in Drug Delivery · Vol. 12, Issue 1, 2025 · pp. 27–30 Read article
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Digital Enablers of Nanomedicine: Pharmaceutical Software Across the Lifecycle of Nanotechnology‑Based Drug Products
Abstract: Nanotechnology‑based drug products have rapidly evolved from laboratory concepts to clinically relevant therapies, yet their development is constrained by complex design variables, stringent quality requirements, and emerging regulatory expectations specific to nanomaterials. Pharmaceutical software now plays a central role in the nanomedicine lifecycle, enabling in silico design of nano‑carriers, simulation of nano–bio interactions, control of nanoscale quality attributes during manufacturing, and systematic tracking of safety signals in real‑world use. Integrated …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 28, Issue 1, 2025 · pp. 11–16 Read article
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Computational Biomodeling: Transforming Drug Design with Advanced Simulations
Abstract: Computational biomodeling has emerged as a transformative approach in the field of drug discovery, significantly enhancing the efficiency and precision of identifying and optimizing potential drug candidates. This article explores the various computational techniques utilized in drug design, including molecular docking, molecular dynamics (MD) simulations, free energy calculations, and virtual screening, and examines how these methods collectively contribute to the drug development process. The integration of these advanced simulations allows …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 3, 2024 · pp. 24–29 Read article